Modeling Employee Creativity Using Artificial Intelligence in the Iranian Banking Industry: A Mixed-Methods Approach
Keywords:
blended approach, banking industry, employee creativity, Artificial intelligence,Abstract
Objective: This study aims to design and validate a comprehensive model explaining how artificial intelligence contributes to enhancing employee creativity in the Iranian banking industry.
Methods and Materials: This applied study adopted a mixed-methods design. In the qualitative phase, data were collected through in-depth semi-structured interviews with 14 academic experts and banking managers selected purposively and analyzed using thematic analysis. In the quantitative phase, a researcher-developed questionnaire based on the extracted qualitative model was administered to 400 banking employees and AI specialists in Tehran, and the data were analyzed using structural equation modeling.
Findings: Confirmatory factor analysis indicated an acceptable fit for all constructs of the proposed model. Path coefficients among model dimensions, challenges, outcomes, strategies, and employee creativity were statistically significant, and all t-values exceeded the critical threshold of 1.96, confirming the hypothesized causal relationships.
Conclusion: The results demonstrate that artificial intelligence, when integrated with appropriate organizational strategies and human resource policies, can function as a critical enabler of employee creativity and a driver of sustainable innovation in the banking sector.
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Copyright (c) 2025 Abdullah Abbasi, Mohammad Khodabakhsh, Danial Saber Samiei (Author)
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